Lectures

Edit 0 22 …
Lecture #
 Date
 Topic
 Lecture
 Reading Material
1
 15/02
 Course Overview , AI - Introduction, History
Introduction to AI Unit 1.pdf

 Tim Jones - Chapter 1
2
 18/02
 Problem solving as search, Search Space
Introduction to AI Unit 2.pdf

 Tim Jones - Chapter 2
3
 22/02
 Depth-first search, Breadth-first search, Best-first Search
Introduction to AI Unit 3.pdf

 Tim Jones - Chapter 2
4
 25/02
 Best-first search, A* Search, Greedy algorithm, Hill climbing
Introduction to AI Unit 4.pdf

 Tim Jones - Chapter 3
5
 01/03
 Search in adversarial games, Minimax Algorithm
Introduction to AI Unit 5.pdf

 Tim Jones - Chapter 4
6
 08/03
 Alpha-beta pruning, OLTP vs OLAP vs Datamining

7
 11/03
 Machine Learning - Classification vs Clustering, Decision Trees
Introduction to AI Unit 6.pdf

 Tim Jones - Chapter 6
Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6
8
 15/03
 Decision Trees, GINI Index, Entropy
Introduction to AI Unit 7.pdf

 Tim Jones - Chapter 6
Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6
9
 15/03
 Decision Trees, GINI Index, Entropy
Tim Jones - Chapter 6
Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6
10
 18/03
 Naive Bayes Classification
Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6
11
 22/03
 Naive Bayes Classification, Metrics for performance evaluation (Accuracy, Precision, Recall etc)


29/03
 Term Exam - 1

12
 01/04
 Neural Networks

13
 05/04
 Neural Networks
Introduction to AI Unit 8.pdf

08/04
 Out of Country ( IranOpen 2011)


12/04
 Out of Country ( IranOpen 2011)

14
 15/04
 Neural Networks

15
 19/04
 Review of Term Exam - I copies,
Clustering

16
 22/04
 Clustering, k-means
Introduction to AI Unit 9.pdf
17
 22/04
 K-means algorithm, Project discussions

18
 26/04
 Logic and Reasoning - Propositional & Predicate logic
Introduction+to+AI+Unit+10.pdf

 http://www.csse.monash.edu.au/~lloyd/tildeLogic/Prolog.toy/Examples/
19
 29/04
 Logic and Reasoning - Propositional & Predicate logic

20
 29/04
 Prolog, Bayesian Network

21
 03/05
 Bayesian Networks
Introduction to AI Unit 11.pdf
22
 13/05
 Inference in Bayesian network

23
 17/05
 d-seperation, Markov Blanket, Serial, Converging, and Diverging connections

24
 20/05
 GeNie, IBAyes, Term Exam-II result
http://genie.sis.pitt.edu/downloads.html
25
 24/05
 Evolutionary Algorithms
Introduction to AI Unit 12.pdf

26
 27/05
 Evolutionary Algorithms

27,28
 29/05
 Computer Vision - Guest Lecture by Mr. Ali Zaidi

29
 31/05
 Swarm Intelligence
Introduction to AI Unit 13.pdf
30
 03/05
 Swarm Intelligence

31
 07/05
 Project Demos